Senior AI Data Engineer – Enterprise Data Platforms

<p><strong>Required Qualifications</strong></p><ul><li>Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.</li><li>10+ years of experience in Data Engineering, Data Architecture, or Data Platform Engineering.</li><li>Strong expertise in cloud platforms such as Azure, AWS, or GCP.</li><li>Deep experience with modern data ecosystems including data lakes, lakehouses, data warehouses, and streaming platforms.</li><li>Experience building and supporting AI/ML data pipelines and feature engineering workflows.</li><li>Familiarity with feature stores, model lifecycle support, and ML operationalization.</li><li>Experience designing and implementing LLM-related data pipelines.</li><li>Strong understanding of data governance, metadata management, lineage, security, and compliance frameworks.</li><li>Proficiency with SQL, Python, Spark, and modern data integration technologies.</li><li>Experience working with distributed data processing frameworks and large-scale datasets.</li></ul><p><strong>Preferred Qualifications</strong></p><ul><li>Experience building data platforms that support AI agents and agentic workflows.</li><li>Knowledge of Retrieval-Augmented Generation (RAG) architectures and semantic search solutions.</li><li>Experience with vector databases, embeddings, and knowledge graph technologies.</li><li>Exposure to data mesh and domain-oriented data architecture principles.</li><li>Experience supporting enterprise AI transformation initiatives.</li><li>Familiarity with MLOps, DataOps, and platform engineering practices.</li><li>Experience working in highly regulated enterprise environments.</li></ul>